Research

Connecting information, energy, and control

My research asks how quantum systems process information under realistic physical constraints. I work across theory, computation, and hardware experiments, with an emphasis on questions that can be stated precisely and tested quantitatively.

Thermodynamics of quantum computation

Quantum processors are physical systems: every computation involves control, energy exchange, noise, and irreversibility. I study work and heat statistics in annealing protocols, the thermodynamic effect of problem encoding, and the relation between computational performance and energetic cost.

Questions: How does a schedule redistribute work and heat? When does an encoding improve success at an unacceptable thermodynamic cost? Which observables can be measured reliably on present hardware?

Quantum annealing and hardware benchmarking

I develop tests that treat a quantum processor as an experimental object rather than an abstract solver. The goal is to isolate what a device does well, where errors enter, and how hardware generations compare under controlled workloads. This includes forward and reverse annealing, physics-inspired QUBO families, and comparisons with classical and quantum-inspired solvers.

Platforms and methods: D-Wave systems, QUBO and Ising formulations, schedule design, statistical inference, exact diagonalization, open-system models, and reproducible benchmarking.

Critical many-body systems and quantum control

Phase transitions provide both a source of useful structure and a challenge for finite-time control. I investigate ground-state and excited-state criticality, non-equilibrium dynamics, work statistics, and control protocols designed around critical regions.

Models and tools: collective-spin models, Ising and Ising–Heisenberg chains, Hubbard systems, tensor networks, exact diagonalization, and phase-space representations.

Quantum information in correlated matter

I use quantum-information measures to identify operational resources in interacting systems. This includes long-distance entanglement and teleportation in Hubbard chains, as well as discrete Wigner functions for resolving phases, correlations, and dynamical transitions.

Aim: connect a formal signature—such as entanglement, discord, or phase-space negativity—to a concrete communication, sensing, or thermodynamic task.

How the pieces fit together

Model

Start from a physical Hamiltonian, control protocol, or constrained optimization problem.

Predict

Derive testable quantities using analytical arguments and numerical simulation.

Run

Execute controlled experiments on quantum hardware or high-performance computing systems.

Audit

Compare models, simulators, hardware generations, and uncertainty-aware performance metrics.